Land cover classification and economic assessment of citrus groves using remote sensing

被引:25
|
作者
Shrivastava, Rahul J. [1 ]
Gebelein, Jennifer L.
机构
[1] Florida Int Univ, SW Environm Res Ctr, Miami, FL 33199 USA
[2] Florida Int Univ, Dept Int Relat, Miami, FL 33199 USA
关键词
agriculture; economy; citrus grove area estimation; Landsat;
D O I
10.1016/j.isprsjprs.2006.10.003
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
The citrus industry has the second largest impact on Florida's economy, following tourism. Estimation of citrus area coverage and annual forecasts of Florida's citrus production are currently dependent on labor-intensive interpretation of aerial photographs. Remotely sensed data from satellites has been widely applied in agricultural yield estimation and cropland management. Satellite data can potentially be obtained throughout the year, making it especially suitable for the detection of land cover change in agriculture and horticulture, plant health status, soil and moisture conditions, and effects of crop management practices. In this study, we analyzed land cover of citrus crops in Florida using Landsat Enhanced Thematic Mapper Plus (ETM+) imagery from the University of Maryland Global Land Cover Facility (GLCF). We hypothesized that an interdisciplinary approach combining citrus production (economic) data with citrus land cover area per county would yield a correlation between observable spectral reflectance throughout the year, and the fiscal impact of citrus on local economies. While the data from official sources based on aerial photography were positively correlated, there were serious discrepancies between agriculture census data and satellite-derived cropland area using medium-resolution satellite imagery. If these discrepancies can be resolved by using imagery of higher spatial resolution, a stronger correlation would be observed for citrus production based on satellite data. This would allow us to predict the economic impact of citrus from satellite-derived spectral data analysis to determine final crop harvests. (C) 2006 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:341 / 353
页数:13
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